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Record W4377861943 · doi:10.1002/exp.20220144

Composite materials based on covalent organic frameworks for multiple advanced applications

2023· review· en· W4377861943 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueExploration · 2023
Typereview
Languageen
FieldMaterials Science
TopicCovalent Organic Framework Applications
Canadian institutionsUniversity of Waterloo
FundersYouth Innovation Promotion AssociationYouth Innovation Promotion Association of the Chinese Academy of SciencesNational Natural Science Foundation of China
KeywordsComposite numberCovalent bondMaterials scienceNanotechnologyComposite materialChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Covalent organic frameworks (COFs) stand for a class of emerging crystalline porous organic materials, which are ingeniously constructed with organic units through strong covalent bonds. Their excellent design capabilities, and uniform and tunable pore structure make them potential materials for various applications. With the continuous development of synthesis technique and nanoscience, COFs have been successfully combined with a variety of functional materials to form COFs-based composites with superior performance than individual components. This paper offers an overview of the development of different types of COFs-based composites reported so far, with particular focus on the applications of COFs-based composites. Moreover, the challenges and future development prospects of COFs-based composites are presented. We anticipate that the review will provide some inspiration for the further development of COFs-based composites.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.080
GPT teacher head0.358
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it